AI RESEARCH
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models
arXiv CS.AI
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ArXi:2605.12374v1 Announce Type: cross Visual latent reasoning lets a multimodal large language model (MLLM) create intermediate visual evidence as continuous tokens, avoiding external tools or image generators. However, existing methods usually follow an output-as-input latent paradigm and yield unstable gains.